| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2016 |
| Язык | английский |
|
Нурутдинова Алсу Рафаиловна, автор
|
| Библиографическое описание на языке оригинала |
IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS. Nurutdinova A.R., Shalagin S.V.// International Journal of Pharmacy & Technology.-2016.-№3.-P. 18926-18935.
|
| Аннотация |
The homogeneous regular and cyclic Markov chains (MC) are widely used in modelling systems for real stochastic
processes, events and phenomena. In particular, the sequence recognition tasks for the MCs generated on the basis of
the ergodic stochastic matrices (ESMs) are of interest. These tasks are relevant and applicable to processing of any
digital signal sequences, analyzing and testing of any discrete devices, identifying of any spoken and written
language.
As part of the task of the discrete Markov processes analyzing, there is a problem of effective recognition methods
and algorithms choice depending on the investigated model parameters, in particular, length of the output sequence,
stochastic matrix dimension and structure, and accuracy of representation of such model elements. In order to address
this issue, this article proposes methods and algorithms for identifying various subclasses of the automate Markov
model based on the generated cyclic Markov chains. |
| Ключевые слова |
cyclic Markov chains |
| Название журнала |
International journal of pharmacy & technology
|
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=141820 |
Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Нурутдинова Алсу Рафаиловна |
ru_RU |
| dc.date.accessioned |
2016-01-01T00:00:00Z |
ru_RU |
| dc.date.available |
2016-01-01T00:00:00Z |
ru_RU |
| dc.date.issued |
2016 |
ru_RU |
| dc.identifier.citation |
IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS. Nurutdinova A.R., Shalagin S.V.// International Journal of Pharmacy & Technology.-2016.-№3.-P. 18926-18935.
|
ru_RU |
| dc.identifier.uri |
https://repository.kpfu.ru/?p_id=141820 |
ru_RU |
| dc.description.abstract |
International journal of pharmacy & technology |
ru_RU |
| dc.description.abstract |
The homogeneous regular and cyclic Markov chains (MC) are widely used in modelling systems for real stochastic
processes, events and phenomena. In particular, the sequence recognition tasks for the MCs generated on the basis of
the ergodic stochastic matrices (ESMs) are of interest. These tasks are relevant and applicable to processing of any
digital signal sequences, analyzing and testing of any discrete devices, identifying of any spoken and written
language.
As part of the task of the discrete Markov processes analyzing, there is a problem of effective recognition methods
and algorithms choice depending on the investigated model parameters, in particular, length of the output sequence,
stochastic matrix dimension and structure, and accuracy of representation of such model elements. In order to address
this issue, this article proposes methods and algorithms for identifying various subclasses of the automate Markov
model based on the generated cyclic Markov chains. |
ru_RU |
| dc.language.iso |
ru |
ru_RU |
| dc.subject |
|
ru_RU |
| dc.title |
IDENTIFICATION ALGORITHMS OF SIMPLE HOMOGENEOUS MARKOV CHAINS OF CYCLIC CLASS AND THEIR COMPLEXITY ANALYSIS |
ru_RU |
| dc.type |
Статьи в зарубежных журналах и сборниках |
ru_RU |
|
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